Abstract
This chapter surveys nonparametric methods for estimation and inference in a panel data setting. Methods surveyed include profile likelihood, kernel smoothers, as well as series and sieve estimators. The practical application of nonparametric panel-based techniques is less prevalent than, for example, say, nonparametric density and regression techniques. It is our hope that the material covered in this chapter will prove useful and facilitate its adoption by practitioners.
Original language | English (US) |
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Title of host publication | Panel Data Econometrics |
Subtitle of host publication | Theory |
Publisher | Elsevier |
Pages | 97-129 |
Number of pages | 33 |
ISBN (Electronic) | 9780128143674 |
ISBN (Print) | 9780128144312 |
DOIs | |
State | Published - Jan 1 2019 |
Keywords
- Data generating process
- Generalized least squares
- Nonparametric estimations
- One-way error component model
- Panel data models models
- Random effects
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- Business, Management and Accounting(all)